Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Huang, Xiao; Wang, Siqin; Zhang, Mengxi; Hu, Tao; Hohl, Alexander; She, Bing; Gong, Xi; Li, Jianxin; Liu, Xiao; Gruebner, Oliver; Liu, Regina; Li, Xiao; Liu, Zhewei; Ye, Xinyue; Li, Zhenlong

doi:10.1016/j.jag.2022.102967

Cited by 24 publications

(11 citation statements)

References 185 publications

(172 reference statements)

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“…Meanwhile, focusing on public health policy and health care education is an essential strategy for responding to public health crisis emergencies in the future ( 60 , 65 ). The utilization of social media data collected from microblogs, WeChat, and Twitter by emergency management departments to mine the information features of public health events to promote digital and smart governance in public health events will be a frontier issue that must be paid attention continually to currently and even in the future ( 3 , 63 , 64 ).…”

Section: Discussionmentioning

confidence: 99%

“…Major public health events are usually characterized by suddenness, complexity, uncertainty, and danger (3). Government emergency management departments can effectively collect big data from social media such as Weibo, WeChat, and Twitter and use specialized tools and methods (natural language processing, sentiment analysis, and text analysis) for data mining and feature extraction of information related to different topics, sentiments, and emotions (63)(64)(65). In turn, governments can respond quickly to achieve optimal public health decisions, thereby mitigating the adverse effects of public health events and promptly returning to normalcy (3).…”

Section: Figurementioning

confidence: 99%

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Research on emergency management of global public health emergencies driven by digital technology: A bibliometric analysis

Chen

Liu

et al. 2023

Front. Public Health

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BackgroundThe frequent occurrence of major public health emergencies globally poses a threat to people's life, health, and safety, and the convergence development of digital technology is very effective and necessary to cope with the outbreak and transmission control of public epidemics such as COVID-19, which is essential to improve the emergency management capability of global public health emergencies.MethodsThe published literatures in the Web of Science Core Collection database from 2003 to 2022 were utilized to analyze the contribution and collaboration of the authors, institutions, and countries, keyword co-occurrence analysis, and research frontier identification using the CiteSpace, VOSviewer, and COOC software.ResultsThe results are shown as follows: (1) Relevant research can be divided into growth and development period and rapid development period, and the total publications show exponential growth, among which the USA, China, and the United Kingdom are the most occupied countries, but the global authorship cooperation is not close; (2) clustering analysis of high-frequency keyword, all kinds of digital technologies are utilized, ranging from artificial intelligence (AI)-driven machine learning (ML) or deep learning (DL), and focused application big data analytics and blockchain technology enabled the internet of things (IoT) to identify, and diagnose major unexpected public diseases are hot spots for future research; (3) Research frontier identification indicates that data analysis in social media is a frontier issue that must continue to be focused on to advance digital and smart governance of public health events.ConclusionThis bibliometric study provides unique insights into the role of digital technologies in the emergency management of public health. It provides research guidance for smart emergency management of global public health emergencies.

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Section: Discussionmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Research on emergency management of global public health emergencies driven by digital technology: A bibliometric analysis

Chen

Liu

et al. 2023

Front. Public Health

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“…It is currently being used to uncover various facets of urban life; however, using such a technocentric approach is mainly tied to a common theme of smart cities (Kourtit et al, 2012 ; Yigitcanlar & Kankanamge, 2022 ). In undertaking urban analytics, social media has been employed as a big data type to present the dynamics of city governance (Kumar et al, 2016 ; Dey & Roy, 2020 ), mobility (Haghighi et al, 2018 ; El-Diraby et al, 2019 ; Osorio-Arjona et al, 2021 ; Huang, Wang, et al, 2022 ), event detection and disaster management (Béjar et al, 2015 ; Moe & Schweidel, 2017 ), urban form, land use (García-Palomares et al, 2017 ) and even evaluating the situation during the COVID-19 pandemic (Hu et al, 2021 ; Huang, Wang, et al, 2022 ).…”

Section: Opportunities In Lbsns To Comprehend Urban Environmentsmentioning

confidence: 99%

“…While there are numerous social media platforms, microblogging platforms such as Twitter are growing in popularity among people and have emerged as a useful source of data analytics (García-Palomares et al, 2017 ; Martí et al, 2019 ; El-Diraby et al, 2019 ; Osorio-Arjona et al, 2021 ; Huang, Wang, et al, 2022 ). By its very nature, micro-blogging provides a succinct and straightforward message of the content (or tweets), thereby reducing noise and allowing for a more in-depth understanding of the topics (Lansley & Longley, 2016 ; Haghighi et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Implications of a Twitter data-centred methodology for assessing commuters’ perceptions of the Delhi metro in India

Agrawal

Kuriakose

2022

Comput.Urban Sci.

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Owing to the onset of the new media age, the idea of e-public participation has proven to be a great complement to the limitations of the conventional public participation approach. In this respect, location-based social networks (LBSN) data can prove to be a game shift in this digital era to offer an insight into the commuter perception of service delivery. The paper aims to investigate the potential of using Twitter data to assess commuters’ perceptions of the Delhi metro, India, by presenting a comprehensive methodology for extracting, processing, and interpreting the data. The study extracts Twitter data from the official handle of the Delhi metro, performs semantic and sentiment analysis to comprehend commuters’ concerns and assesses commuters’ sentiments on the predicted concerns. The paper outlines that the current depth of Twitter data is more inclined to instantaneous responses to grievances encountered. Moreover, the analysis presents that for the data extraction period, the topics ‘Ride Safety’ and ‘Crowding’ have the lowest scores, while ‘Personnel Attitude’ and ‘Customer Interface’ have the highest scores. Further, the paper highlights insights gleaned from Twitter data in addition to the aspects included in the conventional satisfaction survey. The paper concludes by outlining the opportunities and limitations of LBSN analytics for effective public transportation decision-making in India.

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“…Social media platforms enable users around the world to create and share information, forming extensive networks that allow information on specific topics to be collected, stored, and analyzed quickly (X. Huang et al, 2022). The use of social media must be appropriate, in the academic realm, social media can be a medium to help distribute research questionnaires (McCarthy & Bogers, 2022).…”

Section: Introductionmentioning

confidence: 99%

Online Review and Rating on Consumer Purchase Intention: the Moderating Role of Religiosity

Nurillah

Aini²,

Timur³

et al. 2022

JEBA

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Introduction: The rapid development of technology requires business people to adapt, especially in consumer decision-making. This study aims to analyze the effect of online customer reviews and online customer ratings on consumer purchase intentions. Religiosity is the moderating variable in this study. Methods The research method used is quantitative, with PLS-SEM as the evaluation model. Respondents used Muslim, gender male, and female, and were aged 17 years and over, totaling 101 respondents. Where the data was taken by providing an online questionnaire spread on Java Island from April until June 2022. Results: The results showed that online customer reviews did not affect consumers' purchase intentions. On the other hand, online customer ratings influence consumers' purchase intentions. In the moderating variable, religiosity does not have a moderating effect between the dependent and independent variables. Conclusion and suggestion: The rapid development of technology today presents many online platforms. The study's results stated that the Customer Online Review variable did not affect purchase intentions, while the customer online rating variable influenced purchase intention. The researchers advise Muslim fashion business actors who use the media marketplace as a means to sell their products to improve product quality and establish relationships with consumers so that consumers can make repeat purchases. The strategy can be used in developing a Customer Relationship Management (CRM) team.

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Social media mining under the COVID-19 context: Progress, challenges, and opportunities

Cited by 24 publications

References 185 publications

Research on emergency management of global public health emergencies driven by digital technology: A bibliometric analysis

Research on emergency management of global public health emergencies driven by digital technology: A bibliometric analysis

Implications of a Twitter data-centred methodology for assessing commuters’ perceptions of the Delhi metro in India

Online Review and Rating on Consumer Purchase Intention: the Moderating Role of Religiosity

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